I am an AI and backend systems engineer focused on building scalable, secure, production-ready applications, multi-agent AI workflows, and enterprise automation systems. My primary strengths include Python, FastAPI, Django, cloud-native backend architecture, LLM orchestration, and API integrations.
I lead end-to-end delivery of AI-powered products, from system design and data pipelines to deployment, security, observability, and CI/CD. I have built high-volume systems for enterprise operations, service businesses, healthcare, CRM, communications, and intelligent document processing.
My experience includes multi-agent LLM systems, RAG pipelines, vector search, workflow automation, real-time WebSocket applications, and AI voice and chatbot solutions. I work extensively with OpenAI, Claude, Gemini, LangChain, LangGraph, n8n, Postgres, Redis, GCP, AWS, and Docker.
I am also an applied machine learning researcher with experience in intrusion detection, federated learning robustness, anomaly detection, computer vision, and NLP. My undergraduate IDS research was funded by the Ignite National Technology Fund, and I contribute to reproducible, open-source research and software projects.
I care deeply about security, privacy, and reliable engineering. My work includes encrypted secrets management, secure authentication, RBAC, OTP/MFA controls, repository-bound configuration security, and cloud architectures designed for high-scale, multi-tenant deployments.
I am interested in AI and agentic systems, cybersecurity and privacy, healthcare technology, distributed backend systems, enterprise automation, and open-source product development.
